1. Field
This disclosure is generally related to recommender systems. More specifically, this disclosure is related to performing computations on user locations while preserving a user's privacy.
2. Related Art
Advances in portable Internet-enabled computing technologies have made it easier for people to share and receive content while on the go. To take advantage of these portable computing capabilities and people's desire to share information, many entrepreneurs have produced online social-media services that allow people to share their social experiences with the general public in the form of micro-blogs or user-generated reviews. These social-media services also allow people to use their portable devices to search for recommendations for new places to visit or new activities to explore, and to share locations they've visited with others.
However, aside from all the benefits that these services provide to their members, these social-media services are finding it difficult to monetize on their large user base. One common revenue source is to provide paid advertisements or recommendations to users based on the activities they are performing, oftentimes by recommending activities or venues that are close to a person's current location. If the user desires to view recommendations for a location to which the user plans to visit in the near future, the user has to manually fine-tune the search parameters to specify a desired geographic region.
Some recommender systems attempt to model a user's behavior to provide recommendations for activities the user may be interested in performing in the near future. Oftentimes, these recommender systems generate behavior models by analyzing explicit location information for a plurality of users. Unfortunately, this explicit location information can reveal sensitive information pertaining to these users, such as venues that these users have visited and activities these users have performed.